Title
A speech understanding framework that uses multiple language models and multiple understanding models
Abstract
The optimal combination of language model (LM) and language understanding model (LUM) varies depending on available training data and utterances to be handled. Usually, a lot of effort and time are needed to find the optimal combination. Instead, we have designed and developed a new framework that uses multiple LMs and LUMs to improve speech understanding accuracy under various situations. As one implementation of the framework, we have developed a method for selecting the most appropriate speech understanding result from several candidates. We use two LMs and three LUMs, and thus obtain six combinations of them. We empirically show that our method improves speech understanding accuracy. The performance of the oracle selection suggests further potential improvements in our system.
Year
Venue
Keywords
2009
HLT-NAACL (Short Papers)
multiple language model,optimal combination,multiple lms,language model,language understanding model,potential improvement,available training data,new framework,speech understanding accuracy,oracle selection,appropriate speech understanding result,multiple understanding model,speech understanding framework
Field
DocType
Citations 
Training set,Computer science,Oracle,Natural language processing,Artificial intelligence,Language understanding,Machine learning,Language model
Conference
1
PageRank 
References 
Authors
0.38
6
6
Name
Order
Citations
PageRank
Masaki Katsumaru182.23
Mikio Nakano248861.92
Kazunori Komatani379087.95
Kotaro Funakoshi422231.49
Tetsuya Ogata51158135.73
Hiroshi G. Okuno62092233.19